A Mathematical Model of Driver Steering Control Including Neuromuscular Dynamics

2008 ◽  
Vol 130 (3) ◽  
Author(s):  
Andrew J. Pick ◽  
David J. Cole
Keyword(s):  
Path Following ◽  
Linear Quadratic Regulator ◽  
Driver Model ◽  
Steering Wheel ◽  
Steering Control ◽  
Linear Quadratic ◽  
Reflex Action ◽  
Path Following Control ◽  
Steering Torque ◽  
Neuromuscular Dynamics

A mathematical driver model is introduced in order to explain the driver steering behavior observed during successive double lane-change maneuvers. The model consists of a linear quadratic regulator path-following controller coupled to a neuromuscular system (NMS). The NMS generates the steering wheel angle demanded by the path-following controller. The model demonstrates that reflex action and muscle cocontraction improve the steer angle control and thus increase the path-following accuracy. Muscle cocontraction does not have the destabilizing effect of reflex action, but there is an energy cost. A cost function is used to calculate optimum values of cocontraction that are similar to those observed in the experiments. The observed reduction in cocontraction with experience of the vehicle is explained by the driver learning to predict the steering torque feedback. The observed robustness of the path-following control to unexpected changes in steering torque feedback arises from the reflex action and cocontraction stiffness of the NMS. The findings contribute to the understanding of driver-vehicle dynamic interaction. Further work is planned to improve the model; the aim is to enable the optimum design of steering feedback early in the vehicle development process.

scholarly journals Development of an Autonomous Two-Wheeled Vehicle Robot

2011 ◽  
Vol 2-3 ◽  
pp. 390-395
Author(s):  
Minoru Sasaki ◽  
Hidenobu Tanaka ◽  
Satoshi Ito
Keyword(s):  
Control Systems ◽  
Integral Method ◽  
Linear Quadratic Regulator ◽  
Steering Control ◽  
Linear Quadratic ◽  
Wheeled Vehicle ◽  
Roll Rate ◽  
Simulation Results ◽  
Quadratic Integral ◽  
Steering Torque

This paper describes a development of an autonomous two-wheeled vehicle robot. The model of the two-wheeled vehicle using steering control is derived. The control systems are designed by linear quadratic regulator and linear quadratic integral method. Stabilization is achieved by measuring roll angle and roll rate and controlling the steering torque. The experimental results and simulation results show stable running control of the two-wheeled vehicle robot and coincident with each other. The approach is validated through these results.

Vehicle Dynamics Control Based on Linear Quadratic Regulator

2009 ◽  
Vol 16-19 ◽  
pp. 876-880
Author(s):  
Si Qi Zhang ◽  
Tian Xia Zhang ◽  
Shu Wen Zhou
Keyword(s):  
Control Strategy ◽  
Vehicle Dynamics ◽  
Linear Quadratic Regulator ◽  
Active Safety ◽  
Vehicle Stability ◽  
Steering Control ◽  
Linear Quadratic ◽  
Yaw Rate ◽  
Vehicle Dynamics Control ◽  
Yaw Moment

The paper presents a vehicle dynamics control strategy devoted to prevent vehicles from spinning and drifting out. With vehicle dynamics control system, counter braking are applied at individual wheels as needed to generate an additional yaw moment until steering control and vehicle stability were regained. The Linear Quadratic Regulator (LQR) theory was designed to produce demanded yaw moment according to the error between the measured yaw rate and desired yaw rate. The results indicate the proposed system can significantly improve vehicle stability for active safety.

A New Control Strategy to Reduce Steering Torque Without Perceptible Vibration for Vehicles Equipped With Electric Power Steering

2010 ◽  
Vol 132 (5) ◽  
Author(s):  
Masahiko Kurishige ◽  
Osamu Nishihara ◽  
Hiromitsu Kumamoto
Keyword(s):  
Angular Velocity ◽  
Electric Power ◽  
Control Strategy ◽  
Steering Wheel ◽  
Velocity Control ◽  
Steering Control ◽  
Electric Power Steering ◽  
Power Steering ◽  
Wide Range ◽  
Steering Torque

This paper proposes a new electric power steering control strategy, which significantly reduces the effort needed to change the steering direction of stationary vehicles. Previous attempts to reduce undesirable steering vibration have failed to reduce the steering torque because high-assist gains tend to produce oscillation or increase noise sensitivity. Herein, to eliminate this vibration, a new control strategy was developed based on pinion angular velocity control using a newly developed observer based on a simplified steering model. Tests yielded excellent estimations of the pinion angular velocity, and this made it possible to eliminate vibration at all steering wheel rotation speeds. Experiments with a test vehicle confirmed significant steering torque reduction, over a wide range of steering wheel speeds, without vibration transmission to the driver. The proposed control strategy allowed use of an assist gain more than three times higher than is conventional. Additionally, the proposed control strategy does not require supplemental sensors.

Numeric Approach on Optimal Control for the Path Following System in Autonomous Vehicle

2019 ◽  
Author(s):  
Huyao Wu ◽  
Bin Ran
Keyword(s):  
Optimal Control ◽  
Control Strategies ◽  
Autonomous Vehicle ◽  
Path Following ◽  
Linear Quadratic Regulator ◽  
State Feedback Control ◽  
Linear Quadratic ◽  
The Road ◽  
Lqr Controller ◽  
Dynamic Errors

Abstract In this paper, the control strategies for Path Following System (PFS) in autonomous vehicle, which lets vehicle stay in the center of its lane is discussed, we will create a plant mechanical, mathematical and error dynamics model for the study of PFS, which is stabilized by the state-feedback control law, also considers the output where the sensor is made. We apply mainly an optimal control or configure a Linear-quadratic Regulator (LQR) for state space systems and compare it to that based on the Pole Assignment (PA). Combined with a typical operating scenario of the road, we mainly consider static and dynamic errors in the moving process, and how intensely the error fluctuates and how errors are related to the next time. Figures and data show that the LQR controller successfully adjusts and gives appropriate input to let the vehicle approach to centerline, errors and the steering angle required to negotiate a curved road are presented and analyzed, finally relevant conclusions are drawn.

Active Command-Steering Control of Tractor and Three Full Trailers for Tractor-Track Following

2006 ◽  
Author(s):  
Krishna Rangavajhula ◽  
H.-S. Jacob Tsao
Keyword(s):  
High Speed ◽  
Control Strategies ◽  
Linear Quadratic Regulator ◽  
Cost Effective ◽  
Steering Control ◽  
Linear Quadratic ◽  
Amplification Ratio ◽  
High Speeds ◽  
Lqr Controller ◽  
Optimal Linear

A key source of safety and infrastructure issues for operations of longer combination vehicles (LCVs) is off-tracking, which has been used to refer to the general phenomenon that the rear wheels of a truck do not follow the track of the front wheels and wander off the travel lane. In this paper, we examine the effectiveness of command-steering in reducing off-tracking during a 90-degree turn at low and high speeds in an articulated system with a tractor and three full trailers. In command steering, rear front axles of the trailers are steered proportionately to the articulation angle between the tractor and trailing units. We then consider several control strategies to minimize off-tracking and rearward amplification of this system. A minimum rearward amplification ratio (RWA), as a surrogate for minimum off tracking, has been used as the control criterion for medium to high speeds to arrive at an optimal Linear Quadratic Regulator (LQR) controller. As for low speeds, the maximum radial offset between the tractor and trailer 3 is minimized in the design of the controller. Robustness of the optimal controller with respect to tyre-parameter perturbations is then examined. Based on the simulation results, we find that, active command steering is very effective in reducing off tracking at low- as well as high-speed 90-degree turns. To achieve acceptable levels of RWA and off tracking, at least two of the three trailers must be actively command-steered. Among the three two-trailer-steering possibilities, actively steering trailers 1 and 2 is most cost-effective and results in the lowest RWA for medium- to high- speeds (at which RWA is important), and off-tracking is practically eliminated for all speed regimes considered.

Vehicle Stability Improvement by Active Front Steering Control

2007 ◽  
Author(s):  
Deling Chen ◽  
Chengliang Yin ◽  
Li Chen
Keyword(s):  
Time Estimation ◽  
Linear Quadratic Regulator ◽  
Steering System ◽  
Angle Measurement ◽  
Vehicle Stability ◽  
Steering Control ◽  
Linear Quadratic ◽  
Sideslip Angle ◽  
Feedback Parameter ◽  
Active Front Steering

This paper presents the vehicle stability improvement by active front steering (AFS) control. Firstly, a mathematical model of the steering system incorporating vehicle dynamics is analyzed based on the structure of the AFS system. Then feedback controller with linear quadratic regulator (LQR) optimization is proposed. In the controller, the assisted motor in the system is controlled by the combination of feedforward method and feedback method. And the feedback parameter is the yaw rate together with the sideslip angle. Due to the difficulties associated with the sideslip angle measurement of vehicle, a state observer is designed to provide real time estimation to meet the demands of feedback. In the last, the system is simulated in MATLAB. The results show that the vehicle handling stability is improved with the AFS control, and the effectiveness of the control system is demonstrated.

The Active Front Steering Control Strategy Based on Driver Behavior

2013 ◽  
Vol 373-375 ◽  
pp. 1277-1282
Author(s):  
Jian Zhao ◽  
Yun Fu Su ◽  
Bing Zhu ◽  
Peng Fei Wang
Keyword(s):  
Driver Behavior ◽  
Driver Model ◽  
Steering Wheel ◽  
Steering Control ◽  
Active Steering ◽  
Active Front Steering ◽  
Reference Vehicle ◽  
The Stability ◽  
Prediction Control ◽  
Two Degree Of Freedom

Active Front Steering (AFS) is an important application to improve the stability of the vehicle, and the driver characteristic is also an important factor for the vehicle stability. In this article, a driver-behavior-based prediction control algorithm for AFS is proposed. According to the informed road trajectory, the ideal preview driver model is introduced to predict the future steering wheel angle. Based on this, a two-degree-of-freedom (2DOF) reference vehicle model and a PID controller are used to generate active steering control. The algorithm is verified by Carsim and Matlab/Simulink co-simulation, and the results show that trajectory tracking of the vehicle can be guarantee and driver manipulation duty can be reduced.

Development of a neuromuscular driver model with an estimation of steering torque feedback in vehicle steer-by-wire systems

2019 ◽  
Vol 233 (3) ◽  
pp. 657-667
Author(s):  
Amir Gholami ◽  
Majid Majidi
Keyword(s):  
Transfer Functions ◽  
Driver Model ◽  
Steering Wheel ◽  
The Novel ◽  
Muscular System ◽  
Vehicle Model ◽  
Haptic Interaction ◽  
Steer By Wire ◽  
Simulation Results ◽  
Steering Torque

In this paper, a neuromuscular driver model for sensing torque feedback or haptic interaction between the vehicle equipped with steer-by-wire (SBW) system and the driver has been developed. The proposed driver model consists of a preview model and a neuromuscular model. The preview driver model calculates the desired angle of the steering-wheel to follow the path, and the neuromuscular driver model, with the ability of perceiving real-time torque feedback, determines the real angle of the steering-wheel angle according to muscular system transfer functions to follow the desired steering-wheel angle. In order to calculate torques on the steering-wheel, the lateral tyre-road forces are estimated by Kalman filter designed using a linear 2-DOF vehicle model. So, the design of the neuromuscular driver model combined with torque feedback estimation is the main contribution of this paper. The simulation results from TruckSim and Simulink software indicate that the novel designed driver model with torque feedback estimation has an important role in the controlling and steering vehicle to follow the desired paths.

Steering control of six-wheeled vehicles using linear quadratic regulator techniques

2007 ◽  
Vol 221 (10) ◽  
pp. 1231-1240 ◽  
Author(s):  
B-C Chen ◽  
C-C Yu ◽  
W-F Hsu
Keyword(s):  
Linear Quadratic Regulator ◽  
Rear Wheel ◽  
Front Wheel ◽  
Open Loop ◽  
Slip Angle ◽  
Steering Control ◽  
Linear Quadratic ◽  
Integral Control ◽  
Side Slip Angle ◽  
Wheeled Vehicles

The middle- and rear-wheel steering angles of a six-wheeled vehicle need to be coordinated with the front-wheel steering angle to obtain the maximum manoeuvrability. A steering control strategy using the linear quadratic regulator technique with integral control is proposed in this paper such that both zero side-slip angle and target yaw rate following can be achieved simultaneously. An estimator to be used with the control law is also designed to provide the estimate of side-slip angle. AutoSim is used to establish a complex vehicle model with tyre dynamics in MATLAB/Simulink. Both open-loop and closed-loop manoeuvres are performed to evaluate the control performance of the proposed strategy.

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